A review of physical supply and EROI of fossil fuels in China
This paper reviews China’s future fossil fuel supply from the perspectives of physical output and net energy output. Comprehensive analyses of physical output of fossil fuels suggest that China’s total oil production will likely reach its peak, at about 230 Mt/year (or 9.6 EJ/year), in 2018; its total gas production will peak at around 350 Bcm/year (or 13.6 EJ/year) in 2040, while coal production will peak at about 4400 Mt/year (or 91.9 EJ/year) around 2020 or so. In terms of the forecast production of these fuels, there are significant differences among current studies. These differences can be mainly explained by different ultimately recoverable resources assumptions, the nature of the models used, and differences in the historical production data. Due to the future constraints on fossil fuels production, a large gap is projected to grow between domestic supply and demand, which will need to be met by increasing imports. Net energy analyses show that both coal and oil and gas production show a steady declining trend of EROI (energy return on investment) due to the depletion of shallow-buried coal resources and conventional oil and gas resources, which is generally consistent with the approaching peaks of physical production of fossil fuels. The peaks of fossil fuels production, coupled with the decline in EROI ratios, are likely to challenge the sustainable development of Chinese society unless new abundant energy resources with high EROI values can be found.
KeywordsPeak production Fossil fuels Net energy EROI China
China has achieved rapid economic growth since beginning its reform and opening up in the 1980s, with an average annual GDP growth rate of 9.8% from 1978 to 2014 (NBSC 2015). China has now become the second-largest economy in the world after the USA. This great achievement could not have been possible without high energy consumption. From 1978 to 2014, China’s total annual energy consumption increased from just over 570 million tonnes of coal equivalent per year (Mtce/year) to 4260 Mtce/year, representing an average annual growth rate of 5.8% (NBSC 2015). Moreover, most of this energy has been from fossil fuels. In 2014, for example, China’s total fossil fuel consumption was 3780 Mtce/year (coal, 2810 Mtce; oil, 730 Mtce; gas, 240 Mtce), accounting for just under 90% of total energy consumption (the remaining 10% is renewable energy) (NBSC 2015). A large number of studies have indicated that fossil fuels will continue to dominate China’s energy consumption and that demand for these fuels will keep increasing in future, although the rate of this increase may be much lower than in the past, and the structure may also be changed (i.e. stabilizing oil’s share, increasing gas’s share, and reducing coal’s share in primary energy use) (Yuan et al. 2016; IEA 2014). It is thus very important for China to understand its supply status in terms of fossil fuel resources.
Guo and Li (1997) published a peer-reviewed paper which was perhaps the first to discuss the long-term supply status of China’s conventional oil resources. Thereafter, a large number of studies quantitatively investigated the future fossil fuel supply situation of China (e.g. Tao and Li 2007a, b; Feng et al. 2007, 2008a, b). However, the results of these studies differ sharply. For example, while Mohr and Evans (2009) forecast that the peak production of China’s coal resources was likely to be at about 2300 million tonnes per year (Mt/year), the forecast by Li (2012) gave this peak in production being reached at over 6000 Mt/year.
Due to such significant differences, policies relying on only one result may have considerable risk. Therefore, it is crucial to present a comprehensive review of such previous studies to provide a full picture of China’s future supply of fossil fuels to policy makers. A main aim of this paper is thus to provide a full picture of the supply status of China’s fossil fuels by reviewing and analysing currently available literature.
The supply status of fossil fuel resources can be measured from two perspectives: the physical perspective (i.e. physical supply; the volume or weight of physical production of the fuel), and the net energy perspective (i.e. net energy output of the fuel). The reason why we include the net energy perspective in this paper is that for the society, net energy (i.e. subtracting the energy used in production from the energy produced) is the only true energy. However, most current studies have been conducted only from the physical perspective. In 2011, Hu et al. (2011a) were apparently the first to introduce the concepts of net energy and energy return on investment (EROI) into China. Some authors use “energy return on energy invested” (EROEI) for the same concept. Several studies appeared after 2011 which discussed the net energy or EROI for China’s fossil fuel resources (e.g. Hu et al. 2011b, 2013a, b, 2014a; Xu et al. 2014). To fully reflect the supply status of fossil fuel resources, the studies from net energy perspective are also reviewed in this paper.
The potential contribution of this paper is to help the policy makers better understand the future long-term supply of China’s fossil fuel resources by providing all the possible pathways derived from current available literature, discussing the reasons for their difference, and then presenting recommended results.
2 Oil production
China has been a net oil importer since 1993 and a net crude oil importer since 1996 (BP 2015). These events led to concerns being raised about the potential shortage of domestic oil supply, which in turn led to many studies of China’s future oil production. This section covers a comprehensive review of the literature on China’s conventional oil production, non-conventional oil production, and total oil production, and the implications for China’s oil use.
2.1 Conventional oil production
2.1.1 Overall results
Summary of production forecasts for China’s conventional oil resources
Peak production, Mt/year
Guo and Li (1997)
GM and Verhulst models
Shen et al. (2000)
Growth curve model
Jia et al. (2003)
Pang et al. (2005)
Yang et al. (2006)
Zhang and Jia (2007)
Analogy forecast model
Feng et al. (2007)
Hubbert, HCZ and Gen. Weng models
Tao and Li (2007a)
Feng et al. (2008a)
Feng et al. (2008b)
Hubbert, HCZ and Gen. Weng models
Pang et al. (2009)
Tang et al. (2010)
Wang et al. (2015)
Wang et al. (2016a)
Wang and Feng (2016)
Recommended result in this paper*
2.1.2 Reasons for difference
Many reasons could be responsible for these significant differences, but three are believed to be of most important.
The first is that different values of ultimately recoverable resources (URR) were used in the different studies. Table 1 shows that the lowest URR value is 8.2 Gigatonnes (Gt) according to EWG (2007a), while the highest is 24.6 Gt from Wang and Feng (2016). Wang et al. (2015) used the Multi-Cycle Generalized Weng (MCGW) model to forecast that Chinese oil production will peak at 2025, with a peak production of 195 Mt/year. In a separate study, Wang et al. (2016a) used the same MCGW forecast model but obtained different results (with the peak at 2014, and with peak production at 167 Mt/year). The main reason for the difference is that URR was 19.3 Gt in Wang et al. (2015) and lower, at 12.8 Gt, in Wang et al. (2016a).
URR, which is a key input factor for most of forecast models listed in Table 1, is usually defined as the total quantities that can be recovered from discovered and undiscovered deposits (Wang and Feng 2016). Based on this definition, URR can be divided into two parts: one is recoverable quantities from discovered deposits (this part includes cumulative production, reserves, and reserve growth); the other is the potential recoverable quantities from undiscovered deposits (USGS 2000).
One reason of the difference in URR is that non-conventional resources are sometimes also included in statistics of conventional oil resources (Wang et al. 2013a; 2016a). Other reasons are from the assessment process of URR. It is known that the assessment of these recoverable quantities generally needs to consider two factors, i.e. both economic and technical factors (Wang and Feng 2016). The technical factors are usually taken into the resource assessment carried out by Chinese authorities; however, economic factors may be ignored since the primary purpose of resource assessment in China is to know how much resources are there instead of how much resources can be produced by commercial enterprises (Wang et al. 2013a). In this case, assessment results could easily be overestimated if the economic factors are ignored or insufficiently considered. Studies in the literature have shown that the URR values reported by Chinese authorities (URR values higher than 20 Gt in Table 1 are all from various reports by the authorities) probably overestimate the actual URR due to insufficient consideration of economic conditions (Wang et al. 2013a). We should be very careful before using those very high URRs since Hallock et al. (2014) examined the behaviour of petroleum production from some 40 different countries which tended to follow the low URR estimates far more often than medium or high estimates.
The second main reason for the differences in forecasts in Fig. 1 is in the use of different forecast models. Currently, most studies have used different types of curve-fitting models, such as Verhulst model, growth curve model, Weng model, HCZ model, Hubbert model, and Richard’s model shown in Table 1. According to Wang and Feng (2016), the curve shape of models has considerable impact on forecast results and can be divided into symmetric or asymmetric based on their inflection point.1 Asymmetric curves can be further divided into negatively skewed (inflection point > 0.5) and positively skewed shapes (inflection point < 0.5). Generally, the models with a positively skewed curve shape result in lower peak production and lower post-peak decline rate, while models with a negatively skewed curve result in higher peak production and higher post-peak decline rate (Wang and Feng 2016). Brandt (2007) investigated 67 post-peak regions and found that the actual production curves in most regions show a positive skew. Wang et al. (2011) also pointed out the positively skewed curve is better than the symmetric curve for production forecasting. Therefore, it is reasonable to exclude the results estimated by the models with a negatively skewed curve. Luckily, there are no negatively skewed curve-fitting models in Table 1. However, other curve-fitting models with different inflection points may also affect the forecast results. More detailed discussion of the impacts of curve-fitting models on forecast results can be found in Wang and Feng (2016).
The third main reason for the difference in forecasts in Fig. 1 is in the historical production data used. From Table 1, we can see that most forecast models are curve-fitting models, which means the short-term trend of the forecast curve will be affected by historical production data. In China’s oil industry, there are no separate statistics for non-conventional oil production. Therefore, the total historical oil production data are usually seen as the historical conventional oil production by most researchers when they forecast Chinese conventional oil production. That is why many conventional oil forecast curves fit the total historical oil production data well in Fig. 1. The study of Wang et al. (2015) is the first study known to us that breaks out the conventional oil production and non-conventional oil production separately, by collecting the non-conventional oil production data from various sources (See Fig. 1). It can be seen from Table 1 that conventional oil production growth rate becomes significantly lower if non-conventional oil production is excluded from the total oil production. However, at present, it is unrealistic to exclude those estimates [including, for example, Wang and Feng (2016)] that use the total historical production data since they hold a dominant position, and we still lack high-quality conventional oil production data.
2.1.3 Recommended result
Basing policy decisions on such a wide range of forecasts as shown in Fig. 1 is of course difficult. In order to reduce uncertainty, and hence make policy-making somewhat easier, in this paper we have chosen to adopt this “recommended result” approach. We fully accept that reality may turn out different from that indicated by the suggested result, but as indicated elsewhere in this paper there are good reasons for rejecting both the very high and very low forecasts, and here (and in the other cases discussed below) we are reasonably confident that policy decisions formulated at least in part on such “recommended results” are likely to be the most sensible.
In this section, we term the average result of all studies we reviewed as our “recommended result” (see the average conventional oil curve in Fig. 1), except for two types of studies: one is using a URR that does not fully consider the economic factor (i.e. URR values higher than 20 Gt in Table 1); the other is using the negatively skewed curve-fitting models. According to this “recommended result” for China’s conventional oil production, it seems probable that this has peaked in 2014, with a peak production of 170 Mt/year.
2.2 Non-conventional oil supply
Summary of the results of studies for projecting China’s non-conventional oil resources
Wang et al. (2016a) further developed the study of Wang et al. (2015) by specifically including the economic factor in their analyses. Based on this Wang et al. (2016a), China’s total non-conventional oil production is more likely to peak at 2021, at a peak production of close to 65 Mt/year. Wang et al. (2016a) thus also indicate that the actual production of non-conventional oil resources in China is likely to be much lower than the results shown in the high scenario, and higher than the low scenario, of Wang et al. (2015).
In this paper, the median projection, i.e. the forecast of Wang et al. (2016a), is taken as the “recommended result” for non-conventional oil.
2.3 Total oil supply and its implications for China’s oil use
We can then compare this projected total oil production with the forecast for total oil production given in the New Policies Scenario of International Energy Agency (2014). The IEA shows a similar oil production trend. Furthermore, Fig. 3 also indicates the dramatic outcome that results if one compares this paper’s suggested oil production with the historical data, and the IEA’s forecast oil demand. It can be seen from the figure that China’s future oil demand may peak around 2040, with a peak demand of about 780 Mt/year, but before that the oil demand will keep its sharply increasing trend. However, China’s total oil production as indicated in this paper is only likely to be about 170 Mt in 2040. This means that China is expected to see the imbalance between demand and domestic production increasing from 308 Mt/year in 2014 to 610 Mt/year in 2040, with an average annual growth rate of this imbalance of 2.7%. Based on this analysis, oil supply security will remain a serious concern for China. Unless demand for oil falls dramatically, there is no other way to meet this supply gap except by oil imports. In such case, it can be expected that the international oil market will be affected significantly by China’s oil import trend.
3 Gas production
Now we turn to the production of gas. In the history of China’s petroleum industry, the importance of oil was usually higher than that of gas because gas consumption in China was much lower and increased slowly due in part to the lack of infrastructure. However, in 2004 the construction of the first West–East gas pipeline was completed, which has greatly promoted the growth of natural gas consumption. After that, China’s gas consumption began to increase rapidly, with an average annual growth rate of 16.4% between 2004 and 2014 (BP 2015). To meet this soaring gas demand, China’s gas production also experienced a rapid growth during the same period, with an average annual growth rate of 12.2% (BP 2015). However, China’s domestic production still did not fully meet its demand, and in 2007, China for the first time became a net gas importer. Thereafter, many studies began to pay attention to the long-term production potential of China’s gas resources. Similar to the studies of oil production, most studies of gas production are for conventional gas resources; only one study focuses on non-conventional gas resources. Detailed analysis of this topic is given in the following sections.
3.1 Conventional gas production
3.1.1 Overall results
Summary of production forecast for China’s conventional gas resources
Peak production, Bcm/year
Gen. Weng model
Jia et al. (2003)
Pang et al. (2005)
Yang et al. (2006)
Pang et al. (2009)
Li et al. (2009)
Hubbert, HCZ and Gen. Weng models
Wang et al. (2012)
Lin and Wang (2012)
Wang et al. (2013a)
Wang and Lin (2014)
Wang et al. (2016b)
Multi-cycle Hubbert model
Wang et al. (2016c)
Wang and Feng (2016)
Multi-cycle Richard’s model
Recommended result in this paper*
3.1.2 Reasons for difference
The main reasons behind these differences are the same as with conventional oil studies, i.e. URR assumptions, applied forecast models, and the historical production data.
As with oil, the URR gas values from China’s authorities are often significantly higher than those suggested in other literature. For example, according to the 3rd National Oil and Gas Resource Assessment, the URR of China’s conventional gas resources was 22 Tcm (Li et al. 2006), and this number has been used by several studies (see Table 3). However, much of the literature shows that the URR of China’s conventional gas is probably lower, in the 6.7–13.3 Tcm range, with an average value of 10.19 Tcm (Wang et al. 2013a). Similar to conventional oil resources, URR estimates of conventional gas resources also lack full consideration of economic factors. In addition, parts of the tight gas resources are also included in conventional gas resources (Wang et al. 2013a, c).
The models used for gas production forecasting are the same as with conventional oil production modelling, and their impacts on results can be found in Sect. 2.1.
For the historical gas production data, similar to that of the oil production data, there are no separate statistics for non-conventional gas from China’s authorities (Wang et al. 2016c). Current studies therefore usually use total gas production as the conventional gas production. Wang et al. (2016c) first presented a comprehensive investigation of historical production gas data from various sources, and then, for the first time, the conventional gas production data were obtained by excluding the non-conventional gas production from the total production data. As can be seen in Fig. 4, most of the forecast production curve fits the total production data curve well, rather than the conventional gas production curve.
3.1.3 Recommended result
In this paper, as with oil, we select the average result of all the studies we investigated as our hypothesis of a best guess “recommended result”, except those studies that their URR does not fully consider the economic factors (i.e. URR values higher than 20 Tcm in Table 3). From Fig. 4 and Table 3, this recommended result shows that China’s conventional gas production will keep increasing and reach its peak in around 2030, with a peak production of about 190 Bcm/year.
3.2 Non-conventional gas production
As indicated in the previous section, it appears that only one study has been conducted so far that makes a comprehensive investigation of historical production data and resources/reserves data for each type of non-conventional gas resources that of Wang et al. (2016c). Based on these data, Wang et al. (2016c) also carried out what we believe was the first quantitative study of China’s long-term non-conventional gas production. This used the geologic resources supply–demand model (GeRS–DeMo), which is a widely used model for developing the projections of non-conventional fossil fuel production (Mohr and Evans 2010, 2011; Wang et al. 2015). Wang et al. (2016c) develop three scenarios based on different URR assumptions. These are a high scenario (where TRR is treated as the URR), a low scenario (where “cumulative production plus reserves” is used as the URR), and a median scenario (which uses the average of these high and low URRs). It should be noted that resource availability is the only factor considered in Wang et al. (2016c). The potential constraints from environmental issues are not included. Taking shale gas as an example, extracting shale gas may result in many environmental problems, including methane emissions, water use, water pollution, and induced earthquakes (Howarth and Ingraffea 2011; Entrekin et al. 2011; Frohlich 2012). Among these, water issues may be the most significant constraining factor for China shale’s gas development. Hydraulic fracking is usually needed in extracting shale gas resources due to their low permeability, which will consume large amounts of pressurized water. Generally, one shale gas well will use more than 20 thousand cubic metres water, and large-scale development of shale gas will surely have serious impacts on local water resources (Jiang et al. 2014; Hu et al. 2013a, b). However, China itself is facing serious water shortage issues (Zhu et al. 2001), which means that local water availability will be an important constraint for shale gas development. In a report released by the World Resources Institute, China is labelled as “high” average exposure to water stress over its shale gas and shale oil area (Reig et al. 2014). Therefore, if other constrained factors are considered, the forecast results of Wang et al. (2016c) should be seen as the upper bound of the future production and that the actual production will very likely be lower than results shown in Wang et al. (2016c).
Summaries of production forecast for China’s non-conventional gas resources
Peak production, Bcm
Wang et al. (2016c)
Recommended result in this paper*
3.3 Total gas production and its implications on China’s gas use
4 Coal production
4.1 Overall results
Summary of production forecasts for China’s coal resources
Peak production, Mt/year
Tao and Li (2007b)
Mohr and Evans (2009)
Höök et al. (2010)
Lin and Liu (2010)
Patzek and Croft (2010)
Multi-cycle Hubbert model
Wang et al. (2013b)
Modified Hubbert model
Wang et al. (2013c)
Wang and Feng (2016)
Multi-cycle Richard’s model
Bottom-up multi-Hubbert model
Recommended result in this paper*
4.2 Reasons for difference
Many reasons could explain these differences, but we judge the main reason to be the URR assumptions of the different studies.
As indicated above, China’s authorities usually report the country as having very large coal resources. However, these resources have little meaning for production unless they can be produced commercially. The portion that can be produced under existing economic and political conditions with existing technology is usually termed as the “reserve”, which is much more important for modellers than that of the reported total coal resources, since the former is an important part of URR. However, it is very hard to get accurate estimates of recoverable reserves of China’s coal.
The main problem is that the classification system of resources/reserves used by China before 2000 is different from those applied by international institutes. For example, the term of “coal reserves” was usually used to represent the cumulative discovered coal resources before 2000 (Wang et al. 2013b, c), while in most of other systems, the “reserves” must be discovered, recoverable, and remaining. After 2000, to be in line with the international systems, China released a new classification system. However, those old terms are still widely used and convey the wrong information. For example, Tu (2011) still claimed that China’s total coal reserves are 1160 Gt in its report. In addition, some resource/reserve terms in China’s new classification system are still difficult to understand. Taking the new term of “basic reserves” as an example, it is very difficult to find a corresponding term from other classification systems (Wang et al. 2013b, c). According to the authorities’ explanations, only part of these “basic reserves” can be recoverable because they are in deep, thin or otherwise inaccessible places. In addition to the difference in classification systems, another problem is that the resources/reserves data reported by different government agencies are different (Wang et al. 2013b, c). Indeed, sometimes the data reported in different reports by the same agency are also different. For example, the discovered resources in 2010 are reported to be 211.5 Gt by the Ministry of Land and Resources of China (MLR) in one report; however, this number is reported to be 57.51 Gt by the MLR in another report. Furthermore, many international reserves statistics from other institutes have reported incorrect data. For example, China’s proved coal reserves as reported by both the World Energy Council (WEC) and the BP Statistical Review have remained at 114.5 Gt for years, which itself is an incorrect estimate number (Lin and Liu 2010; Wang et al. 2013b, c). It should be noted in Fig. 7 that early coal forecasts tend to underestimate the potential for coal production to increase, and one key reason is that their URRs are estimated based on WEC and BP’s data.
4.3 Recommended result
Wang et al. (2013b, c) made a detailed study of China’s coal classification system and resources/reserves data. Based on their analyses, China’s coal URR is likely to be about 225 Gt. The URR values shown in Table 5 that are higher than 225 Gt are estimates based on the “basic reserves” or the average value “reserves” and “basic reserves”. Therefore, in this paper, our suggested result for China’s coal production is estimated to be the upper-bound value of all studies except those studies whose URR is higher than 225 Gt (See Fig. 7).
According to this “recommended result”, China’s coal production ability could keep increasing until to about 2020, and the maximum production ability will be about 4400 Mt/year.
4.4 Implications on China’s coal use
The three demand curves shown in Fig. 8 reflect three opinions on China’s future coal demand trends. Some scholars believe that China’s coal demand will keep increasing until China finishes its major transition to full industrialization (Shealy and Dorian 2010; Feng 2012) (see the red line in Fig. 8). Some scholars from climate institutes claimed that China’s coal demand must decline immediately to reduce carbon emissions and hence achieve China’s promise that carbon emissions will peak no later than 2030 (Green and Stern 2014) (see black line in Fig. 8). Most scholars or institutes think both of the above two opinions are unrealistic, claiming that coal is the only reliable energy source due to its abundant resources. A realistic way they suggest solving the environmental problem is to use coal resources in new ways (such as with clean coal technologies) instead of abandoning the coal resources completely. These experts think that China’s coal consumption will keep increasing with a very slow growth rate, or stay at a plateau, until China finishes its full industrialization (NDRC 2009; LBNL 2009) (similar with the green line shown in Fig. 8, or maybe slightly lower).
However, all these above discussions on coal demand do not fully considered the potential supply constraints of China’s coal resources. From Fig. 8, we can see that the high demand trend in the Current Policies Scenario is difficult to meet from domestic coal supply. Considering these likely domestic coal supply constraints, a possible pathway for future coal demand is to increase very slowly or stay on a plateau before 2035, and then decline steadily (hence follow a path lower than the coal demand trend shown in the green line in Fig. 8).
5 EROI analysis for China’s fossil fuels
Studies shown in the previous sections mainly focus on the physical outputs of fossil energy, i.e. emphasizing the final energy outputs without considering the energy inputs in the process of energy exploitation. Net energy or energy surplus (i.e. energy output minus energy input to get that energy) is the true value of energy resources and is the correct measure of the real energy contribution to society (Lambert et al. 2014). EROI is a suitable tool for net energy analysis, and it can be normally calculated on the basis of thermal equivalence by dividing energy outputs by energy inputs (Hall et al. 1981, 1986; Cleveland et al. 1984).
From Fig. 9, we can see that the EROIs of China fossil fuels show a declining trend mainly due to the depletion of shallow-buried coal resources and to the move away from conventional oil and gas resources. The declining trend for coal’s EROI is more obvious than those of China’s oil and gas, and the specific values of EROI for each fossil fuel are different. As can be seen from Fig. 9, China’s coal resources have had the highest EROI in the past, and its EROI value is estimated to be 29.6:1 in 2012 (Hu et al. 2013a, b). The EROI of China’s overall oil and gas is much lower than that of coal and was forecast to be 9.9 in 2012 (Hu et al. 2013a, b).
It should be noted that the blue line in Fig. 9 represents the total oil and gas industry. There are no separate studies in China for the individual oil and gas industries at a national level because oil and gas are usually concomitant and their input data are also mixed. If the input data for oil and gas can be collected separately, it can be expected that the EROI of oil will be lower than gas since China’s oil industry has been developed for years and has entered its mid- and late period, while gas industry is still in its middle and early period. Generally, the inputs during the mid- and later period are much larger. As an example, we can use the case of the Daqing oil field. Daqing oil field, which is the largest oil field in China, has been developed for nearly 60 years and has entered its late period. To maintain its production level or reduce its production decline rate, the Daqing oil field has been using more advanced enhanced oil recovery (EOR) methods for many years, such as polymer flooding and the alkaline-surfactant-polymer (ASP) flooding method (Wang et al. 2016a). All these new methods are well known for their high cost and environmental impact, which in turn leads to lower EROI and declines in the Daqing oil field’s EROI. From Fig. 9, we can see that the EROI for Daqing oil field is only 6.4 in 2012 (Hu et al. 2014b), which is the lowest value in our collected data.
This paper reviews a wide range of studies of China’s supply of fossil fuels from two aspects: one is the physical supply, and the other is the net energy supply. Several conclusions can be summarized, as follows:
Firstly, China’s conventional oil production appears most probably to have peaked in 2014, with a peak production of 170 Mt/year. Current observed growth in China’s total oil production is thus mainly from non-conventional oil resources. A further analysis of future non-conventional oil production shows that the production growth in China’s non-conventional oil resources will possibly end as early as 2021; thereafter, its production of this class of oil will also decline. As a result, China’s total oil production is forecast to peak in 2018, with a peak production level of 230 Mt/year.
Secondly, China’s conventional gas production is forecast to keep increasing and reach its peak during 2025–2030, with a peak production of 180–190 Bcm/year. Non-conventional gas resources are forecast to achieve a rapid development, and we see their production as likely being able to increase until around 2058, reaching a peak production at 270 Bcm/year. Due to this great development of non-conventional gas resources, the total gas production in China will keep increasing until reaching a peak at 350 Bcm/year in 2040.
Thirdly, a reasonable estimate of the upper bound on China’s coal production indicates that this is likely to peak at about 4400 Mt/year by 2020 or so. This finding is likely to be a surprise to most experts from China’s coal industry, since the mainstream opinion is that China is rich in coal, and there is no need to worry about supply shortage of its coal resources.
Fourthly, by comparing China’s fossil fuel supply and demand, we can see that supply constraints of oil and gas resources are likely to have very serious impacts on China’s oil and gas security. The gap between domestic production and demand of oil and gas is forecast to increase rapidly. In addition, coal supply constraints show that that a high coal demand scenario is unlikely to be met from purely domestic production. This is because by considering the supply constraints of China’s coal resources, a probable pathway for China’s future coal demand appears to be a very slow increase in production, or staying at a plateau, up to 2035 and then to decline steadily thereafter.
Fifthly, three key factors can be used to explain the significant differences among current fossil fuel forecast studies. These are the URR assumptions used, the models applied, and the historical production data used. The problem of the applied models can in principle be solved by technical methods. However, the problems with reliable URR estimates, and historical production data, are usually very hard to solve for a number of reasons, including incomparable classification systems of resources/reserves, and incomplete statistical historical production data (no separate statistics on non-conventional oil and gas resources; and for example different data reported by the same government agency). To better understand the future production of China’s fossil fuels, it is crucial for China to improve its data assessment and statistical systems.
Finally, studies of China’s fossil fuel supply from the crucial perspective of net energy are summarized here for the first time. A steady declining trend can be observed in the EROI ratios of both the coal and the oil and gas industries due to the depletion of shallow-buried coal resources and of conventional oil and gas resources. This declining EROI trend is generally consistent with the approaching of peaks of physical production of the fossil fuels. The declining EROI ratios in turn mean more and more energy inputs are needed to produce the same amount of energy output. Such a situation will be unsustainable for Chinese society if China cannot find new and abundant energy sources with high EROI values, or find some way to support one and one half billion people at a dignified standard of living by much less energy-intensive means.
The inflection point is where the curvature changes sign, and this point coincides with the maximum production level. The production in symmetric models always peaks when 50% of the URR has been depleted, i.e., the inflection point of symmetric models = 0.5. Asymmetric models can have inflection points that occur at an arbitrary depletion level (Wang and Feng 2016).
This study has been supported by the National Natural Science Foundation of China (Grant Nos. 71503264, 71373285, 71303258), Humanities and Social Sciences Youth Foundation of the Ministry of Education of China (Grant Nos. 15YJC630121, 13YJC630148), Science Foundation of China University of Petroleum, Beijing (No. 2462014YJRC024) and the Major Program of the National Social Science Found of China (Grant No. 13&ZD159).
- BP. Statistical review of world energy 2015. London: BP plc; 2015.Google Scholar
- Energy Watch Group (EWG). Crude oil—the supply outlook. 2007a. EWG-SeriesNo. 3/2007. http://www.energywatchgroup.org/fileadmin/global/pdf/EWG_Oilreport_10-2007.pdf.
- Energy Watch Group (EWG). Coal: resources and future production. 2007b. Technical report EWG-Series No 1/2007, Energy Watch Group.Google Scholar
- Feng LY, Li J, Pang X, et al. Peak oil models forecast china’s oil supply, demand. Oil Gas J. 2008b;1:43–7.Google Scholar
- Feng LY. Analysis on coal import origin of China. Master’s thesis for Inner Mongolia University. 2012.Google Scholar
- Guo BS, Li HY. Forecast on China’s oil production in the initial 21st century. Geol Technol Manag. 1997;5:51–3 (in Chinese).Google Scholar
- Green F, Stern N. An innovative and sustainable growth plan for China: a critical decade. Policy paper for Grantham Research Institute on climate change and the environment. 2014. http://www.lse.ac.uk/GranthamInstitute/wp-content/uploads/2014/05/An-Innovative-and-Sustainable-Growth-Path-for-China-A-Critical-Decade1.pdf.
- Hall CAS, Cleveland CJ, Berger M. Energy return on investment for United States petroleum, coal, and uranium. In: Mitsch W, editor. Energy and ecological modeling. Amsterdam: Elsevier; 1981. p. 715–24.Google Scholar
- Hall CAS, Kaufmann R, Cleveland CJ. Energy and resource quality: the ecology of the economic process. New York: Wiley; 1986.Google Scholar
- Hu CY. Initial discussion on China’s gas recoverable reserves and peak production forecast. Mar Orig Pet Geol. 1999;4(3):1–5 (in Chinese).Google Scholar
- Hu WH, Hu YH, Yang YW. Analysis of the impacts of shale gas development on water resources, water engineering and water environment in Fuling area. In: Proceedings of the seminar of “Reasonable configuration and efficient utilization of water resources, serving the urban and rural development” organized by Chongqing Hydraulic Engineering Society; 2013b. 1 Aug 2013. (in Chinese). Google Scholar
- International Energy Agency (IEA). World Energy Outlook (WEO). Paris: IEA; 2014.Google Scholar
- Lawrence Berkeley National Laboratory (LBNL). China’s coal: demand, constraints, and externalities. Berkeley: LBNL; 2009.Google Scholar
- Li JM, Liu SZ, Li DX, et al. Natural gas exploration in China: current status and development trends. China Oil Gas. 2006;13(2):14–7 (in Chinese).Google Scholar
- Li MQ. Peak energy and the limits to China’s economic growth: prospect of energy supply and economic growth from now to 2050. Political Economy Research Institute working paper; 2008.Google Scholar
- Li SQ. The study of future supply of China’s coal resources and its impacts. Master’s thesis for China University of Petroleum, Beijing. June 2016 (in Chinese).Google Scholar
- National Development and Reform Commission (NDRC). 2050 China energy and CO2 emissions report. Beijing: Science Press; 2009 (in Chinese).Google Scholar
- National Bureau of Statistics of China (NBSC). China statistical yearbook 2015. Beijing: China Statistics Press; 2015 (in Chinese).Google Scholar
- Pang XQ, Meng QY, Bai GP, et al. The challenge and countermeasures brought by the shortage of oil and gas in China. Presentation at ASPO-4, Lisbon Portugal; 2005.Google Scholar
- Reig P, Luo TY, Proctor JN. Global shale gas development: water availability and business risks. Washington, D. C.: World Resources Institute; 2014.Google Scholar
- Tu JJ. Industrial organization of the Chinese coal industry. Working paper #103; July 2011. http://carnegieendowment.org/files/China_Coal_Value_Chain_Kevin_Tu3.pdf.
- U.S. Geological Survey (USGS). World Petroleum Assessment 2000. U.S. Geological Survey Digital Data Series—DDS-60; 2000. http://pubs.usgs.gov/dds/dds-060/.
- Wang T, Sun CW, Li XM. China’s natural gas production forecast and its price reform. J Financ Res. 2012;3:43–56 (in Chinese).Google Scholar
- Zhang YF, Jia CZ. History contrast and analysis of oil reserves and production increase in China and USA. Research report by Post-doctoral of Research Institute of Petroleum Exploration and Development, PetroChina; 2007. (in Chinese). Google Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.